Offensive Word Scoring With Adaptive Cultural Thresholds
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Solution Overview
Problem
Existing systems lack the ability to effectively identify and manage offensive language across diverse cultural and individual thresholds, leading to inconsistent content filtering and potential violations of local regulations.
Innovation Solution
A computer-implemented system that calculates the offensiveness score of candidate words by comparing them to a list of offensive words using distance metrics and severity scores, allowing users and administrators to set personalized thresholds for filtering offensive content based on cultural norms and individual preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If censorship is used to suppress or control materials that are considered obscene or offensive, then harmful factors are reduced, but adaptability deteriorates because content that is acceptable in one culture may be blocked in another
Solution Approach 1:
The system implements location-specific offensiveness thresholds that adapt to local cultural norms and regulations. Different geographical locations can have different threshold values, allowing content to be evaluated according to local standards rather than a single universal standard, thereby resolving the conflict between filtering harmful content and maintaining cultural adaptability
Solution Approach 2:
The offensiveness threshold is made dynamic and adjustable rather than fixed. The system allows thresholds to be modified based on location, user preferences, and context, enabling flexible adaptation to different cultural and regulatory environments while maintaining effective content filtering
2Ease of operation
If a fixed offensiveness threshold is applied to all users and locations, then ease of operation is improved, but adaptability deteriorates because it cannot accommodate different cultural norms and individual preferences
Solution Approach 1:
The system provides a universal threshold management mechanism that serves multiple functions: it can operate with default thresholds for simplicity, allow location-based adaptation for cultural sensitivity, and support individual user customization for personal preferences. This multi-functional approach resolves the contradiction between ease of operation and cultural adaptability
3Adaptability or versatility
If content filtering is made highly adaptive to individual preferences and cultural norms, then adaptability is improved, but device complexity increases due to multiple threshold settings and configurations
Solution Approach 1:
The system pre-configures location-based thresholds and default settings before users need them. When a user accesses the system, their location is automatically detected and the appropriate thresholds are applied without requiring manual configuration. This preliminary setup reduces the perceived complexity for users while maintaining high adaptability
Solution Approach 2:
The system automatically manages threshold configurations based on user location and preferences without requiring extensive manual intervention. Users can simply access their preferences to view or modify thresholds, and the system handles the complex configuration logic automatically, reducing operational complexity while maintaining flexibility
Data Source
AI summary
Computer-implemented systems and methods are provided for identifying language that would be considered obscene or otherwise offensive to a user or proprietor of a system. A plurality of offensive words are received, where each offensive word is associated with a severity score identifying the offensiveness of that word. A string of words is received. A distance between a candidate word and each offensive word in the plurality of offensive words is calculated, and a plurality of offensiveness scores for the candidate word are calculated, each offensiveness score based on the calculated distance between the candidate word and the offensive word and the severity score of the offensive word. A determination is made as to whether the candidate word is an offender word, where the candidate word is deemed to be an offender word when the highest offensiveness score in the plurality of offensiveness scores exceeds an offensiveness threshold value.